Create README.md

README.md

@@ -0,0 +1,46 @@
+---
+language:
+- ar
+
+datasets:
+ - ASTD
+
+tags:
+ - labr
+
+widget:
+- text: "العنف والقتل في محيط العالم في زياده يوميا"
+- text: "الصداقه تزرع الحياه ازهارا"
+
+---
+
+# BERT-LABR unbalanced
+Arabic version bert model fine tuned on ASTD dataset balanced version to identify twitter sentiments in Arabic language MSA dialect .
+
+## Data
+The model were fine-tuned on ~63000 book reviews in arabic using bert large arabic
+
+
+## Results
+| class    | precision | recall | f1-score | Support |
+|----------|-----------|--------|----------|---------|
+| 0        | 0.9328    | 0.9398 | 0.9363   | 133     |
+| 1        | 0.9394    | 0.9323 | 0.9358   | 133     |
+| Accuracy |           |        | 0.9361   | 266     |
+
+
+
+
+
+## How to use
+
+You can use these models by installing `torch` or `tensorflow` and Huggingface library `transformers`. And you can use it directly by initializing it like this:  
+
+```python
+from transformers import AutoModelForSequenceClassification, AutoTokenizer
+
+model_name="mofawzy/BERT-ASTD"
+model = AutoModelForSequenceClassification.from_pretrained(model_name,num_labels=2)
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+
+```